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Updated: May 24, 2026
De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
Published on: February 18, 2022
i-rDNA: alignment-free algorithm for rapid in silico detection of ribosomal gene fragments from metagenomic sequence
Monzoorul Haque Mohammed1, Tarini Shankar Ghosh, Sudha Chadaram
1Bio-Sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Hyderabad 500 081, Andhra Pradesh, India.
Background:
Obtaining accurate estimates of microbial diversity using rDNA profiling is the first step in most metagenomics projects. Consequently, most metagenomic projects spend considerable amounts of time, money and manpower for experimentally cloning, amplifying and sequencing the rDNA content in a metagenomic sample. In the second step, the entire genomic content of the metagenome is extracted, sequenced and analyzed. Since DNA sequences obtained in this second step also contain rDNA fragments, rapid in silico identification of these rDNA fragments would drastically reduce the cost, time and effort of current metagenomic projects by entirely bypassing the experimental steps of primer based rDNA amplification, cloning and sequencing. In this study, we present an algorithm called i-rDNA that can facilitate the rapid detection of 16S rDNA fragments from amongst millions of sequences in metagenomic data sets with high detection sensitivity.
Results:
Performance evaluation with data sets/database variants simulating typical metagenomic scenarios indicates the significantly high detection sensitivity of i-rDNA. Moreover, i-rDNA can process a million sequences in less than an hour on a simple desktop with modest hardware specifications.
Conclusions:
In addition to the speed of execution, high sensitivity and low false positive rate, the utility of the algorithmic approach discussed in this paper is immense given that it would help in bypassing the entire experimental step of primer-based rDNA amplification, cloning and sequencing. Application of this algorithmic approach would thus drastically reduce the cost, time and human efforts invested in all metagenomic projects.
Availability:
A web-server for the i-rDNA algorithm is available at http://metagenomics.atc.tcs.com/i-rDNA/
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